تحقیقات کاربردی علوم جغرافیایی

تحقیقات کاربردی علوم جغرافیایی

Attribution of Climate Change to the extreme snow falls of mazandaran province (stochastic climate modeling using lorenz-63)

نویسندگان
zahra hejazizadeh
Roya Arefyan
10.22034/jgs.2025.11672
چکیده
The aim of this study was to attribute climate change to the occurrence of extreme snowfall in Mazandaran Province, located in northern Iran along the southern shores of the Caspian Sea and in the vicinity of the Alborz Mountains. This region is not typically prone to extreme snowfall; therefore, such events can cause significant damage to the region's infrastructure. The study focused on the winter season (DJF) during the period from 1987 to 2017. The corresponding calculations were performed for two parallel counterfactual worlds: one without external forcing and one factual world with external forcing, within the framework of stochastic climate modeling. This was achieved using the chaotic dynamical three-dimensional Lorenz-63 (Lorenz-63) model. The two study worlds were defined on the basis of the deterministic LM-63 and stochastic SLM-63 climate models, respectively. The Fokker–Planck equation was used to implement the temporal evolution of the probability density function (PDF) within the model. Conditional probability and the Bayesian framework constitute the methodological foundations of this study. The model belongs to the class of state-space models and employs Bayesian recursive estimation. Together, these elements form the basis of the Ensemble Kalman Filter (EnKF), a nonlinear filtering approach applied to the nonlinear dynamical model used in this study. An effort was made to address all relevant aspects of the problem on the basis of sound mathematical, epistemological, and physical foundations. All computations were performed using GIS, MATLAB, Mathematica, and Maple.
کلیدواژه‌ها
Attribution
stochastic process
Lorenz-63
Ensemble Kalman Filter (EnKF )
causal (counterfactual) theory

عنوان مقاله English

ATTRIBUTION OF CLIMATE CHANGE TO THE EXTREME SNOW FALLS OF MAZANDARAN PROVINCE (stochastic climate modeling using Lorenz-63)

نویسندگان English

zahra hejazizadeh
Roya Arefyan
چکیده English

The aim of this study was to do attribution of climate change to the extreme snow fall of Mazandaran province in the northern part of Iran and southern shores of the Caspian Sea in the vicinity of Alborz mountains. The area is not prone to extreme snow fall or even snow fall then this phenomenon has had great damages to the infrastructures of the region. The study is performed on the time interval of 1987-2017in winter time (DJF). Corresponding calculation is done for two parallel worlds of counterfactual i.e. without external forcing and factual with external forcing in the context of stochastic climate modeling. This is done by the chaotic dynamical 3-D model Lorenz-63. Then the two worlds of study are defined on the basis of LM-63 and SLM-63 as deterministic and stochastic climate models. Fakher- Planck equation had the role of implementing time evolution of the PDF into the modal. The conditional probability and Bayesian framework is the preliminaries of the method of this study. The model is belonging to the space state models and Bayesian recursive estimation. These all is the basis of the EnKF as nonlinear filtering approach to the nonlinear dynamical model of this study. It is tried to bring down all the related situation associated with the issue on the basis of sound mathematical, epistemological and physical foundations. All the computations are done on the environment of GIS, Matlab, Mathematica and Maple. Then causal theory of pearl (2000) is used as the evidence of verification for the whole process. The final results showed that the extreme snow of Mazandaran province is attributable to the climate forcing defined for the study 0.8978 in its PN causation, 0.1942 in its PS causation and 0.4519 in its PNS causation.

کلیدواژه‌ها English

Attribution
stochastic process
Lorenz-63
Ensemble Kalman Filter (EnKF )
causal (counterfactual) theory
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تحقیقات کاربردی علوم جغرافیایی
دوره 25، شماره ویژه
زمستان 1404
زمستان 1404
صفحه 1-22